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Facial recognition reveals political party…

Portland moves to ban technology…

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Facial recognition reveals political party…

Source: TechCrunch.com

Researchers have created a machine learning system that they claim can determine a person’s political party, with reasonable accuracy, based only on their face. The study, from a group that also showed that sexual preference can seemingly be inferred this way, candidly addresses and carefully avoids the pitfalls of “modern phrenology,” leading to the uncomfortable conclusion that our appearance may express more personal information that we think.

The study, which appeared this week in the Nature journal Scientific Reports, was conducted by Stanford University’s Michal Kosinski. Kosinski made headlines in 2017 with work that found that a person’s sexual preference could be predicted from facial data.

The study drew criticism not so much for its methods but for the very idea that something that’s notionally non-physical could be detected this way. But Kosinski’s work, as he explained then and afterwards, was done specifically to challenge those assumptions and was as surprising and disturbing to him as it was to others. The idea was not to build a kind of AI gaydar — quite the opposite, in fact. As the team wrote at the time, it was necessary to publish in order to warn others that such a thing may be built by people whose interests went beyond the academic:

“We were really disturbed by these results and spent much time considering whether they should be made public at all. We did not want to enable the very risks that we are warning against. The ability to control when and to whom to reveal one’s sexual orientation is crucial not only for one’s well-being, but also for one’s safety.”

“We felt that there is an urgent need to make policymakers and LGBTQ communities aware of the risks that they are facing. We did not create a privacy-invading tool, but rather showed that basic and widely used methods pose serious privacy threats.”

Similar warnings may be sounded here, for while political affiliation at least in the U.S. (and at least at present) is not as sensitive or personal an element as sexual preference, it is still sensitive and personal. A week hardly passes without reading of some political or religious “dissident” or another being arrested or killed. If oppressive regimes could obtain what passes for probable cause by saying “the algorithm flagged you as a possible extremist,” instead of for example intercepting messages, it makes this sort of practice that much easier and more scalable.

The algorithm itself is not some hyper-advanced technology. Kosinski’s paper describes a fairly ordinary process of feeding a machine learning system images of more than a million faces, collected from dating sites in the U.S., Canada and the U.K., as well as American Facebook users. The people whose faces were used identified as politically conservative or liberal as part of the site’s questionnaire.

The algorithm was based on open-source facial recognition software, and after basic processing to crop to just the face (that way no background items creep in as factors), the faces are reduced to 2,048 scores representing various features — as with other face recognition algorithms, these aren’t necessary intuitive things like “eyebrow color” and “nose type” but more computer-native concepts.

The system was given political affiliation data sourced from the people themselves, and with this it diligently began to study the differences between the facial stats of people identifying as conservatives and those identifying as liberal. Because it turns out, there are differences.

Of course it’s not as simple as “conservatives have bushier eyebrows” or “liberals frown more.” Nor does it come down to demographics, which would make things too easy and simple. After all, if political party identification correlates with both age and skin color, that makes for a simple prediction algorithm right there. But although the software mechanisms used by Kosinski are quite standard, he was careful to cover his bases in order that this study, like the last one, can’t be dismissed as pseudoscience.

The most obvious way of addressing this is by having the system make guesses as to the political party of people of the same age, gender and ethnicity. The test involved being presented with two faces, one of each party, and guessing which was which. Obviously chance accuracy is 50%. Humans aren’t very good at this task, performing only slightly above chance, about 55% accurate.

The algorithm managed to reach as high as 71% accurate when predicting political party between two like individuals, and 73% presented with two individuals of any age, ethnicity or gender (but still guaranteed to be one conservative, one liberal).

Getting three out of four may not seem like a triumph for modern AI, but considering people can barely do better than a coin flip, there seems to be something worth considering here. Kosinski has been careful to cover other bases as well; this doesn’t appear to be a statistical anomaly or exaggeration of an isolated result.

The idea that your political party may be written on your face is an unnerving one, for while one’s political leanings are far from the most private of info, it’s also something that is very reasonably thought of as being intangible. People may choose to express their political beliefs with a hat, pin or t-shirt, but one generally considers one’s face to be nonpartisan.

If you’re wondering which facial features in particular are revealing, unfortunately the system is unable to report that. In a sort of para-study, Kosinski isolated a couple dozen facial features (facial hair, directness of gaze, various emotions) and tested whether those were good predictors of politics, but none led to more than a small increase in accuracy over chance or human expertise.

“Head orientation and emotional expression stood out: Liberals tended to face the camera more directly, were more likely to express surprise, and less likely to express disgust,” Kosinski wrote in author’s notes for the paper. But what they added left more than 10 percentage points of accuracy not accounted for: “That indicates that the facial recognition algorithm found many other features revealing political orientation.”

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Business

BITCOIN GOES BOOM ^ ABOVE 50K 1st TIME E V E R.

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BITCOIN GOES BOOM ^ ABOVE 50K 1st TIME E V E R.

KEY POINTS

  • Bitcoin surged to an all-time high of more than $50,000 on Tuesday.
  • Large firms like Tesla, Mastercard and BNY Mellon have shown support for cryptocurrencies.
  • Many crypto investors believe the current bull run is different to a late 2017 bubble.

MORE… CNBC. 😉

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European Central Bank Calls for Global Regulations on Bitcoin…

President of the European Central Bank Christine Lagarde has called for global regulations on Bitcoin, labeling the cryptocurrency “reprehensible.”

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European Central Bank Calls for Global Regulations on Bitcoin…

ZERO HEDGE

President of the European Central Bank Christine Lagarde has called for global regulations on Bitcoin, labeling the cryptocurrency “reprehensible.”

Lagarde made the comments during a Reuters Next conference earlier today, during which she asserted that Bitcoin was not a currency.

“When you look at the most recent developments upward, and now the recent downward trend … for those who have assumed that it might turn into a currency, terribly sorry but this is an asset and it is a highly speculative asset,” she said.

The former head of the IMF, who was previously found guilty of financial negligence by a French court over a €403 million arbitration deal in favor of businessman Bernard Tapie, went on to accuse Bitcoin of being heavily embroiled in criminal activity.

“(Bitcoin) has conducted some funny business and some interesting and totally reprehensible money laundering activity,” said Lagarde.

The ECB head went on to call for Bitcoin to be regulated by financial authorities.

“There has to be regulation. This has to be applied and agreed upon […] at a global level because if there is an escape that escape will be used,” she said.

Globalists and technocrats have long begrudged Bitcoin because it is decentralized and therefore impossible to come under the control of centralized financial institutions. The cryptocurrency has also provided a refuge for dissidents who have been deplatformed by regular financial services and institutions over their politics.

Bitcoin recently soared to a record high above $41,000 dollars but has since fallen back to around $35,000 dollars.

After the cryptocurrency previously hit a record high of above $17,000 dollars at the end of 2017 it then sank bank to around $3,000, emphasizing the wild volatility of the asset.

However, numerous analysts are predicting that growing debt, record money printing and hyperinflation could see Bitcoin soar into the hundreds of thousands over the next year.

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CNN: Venice is watching tourists’ every move… Smart city technology deployed…

“This is the brain of the city”

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CNN: Venice is watching tourists’ every move… Smart city technology deployed…

(CNN) — They’re watching you, wherever you walk. They know exactly where you pause, when you slow down and speed up, and they count you in and out of the city.

What’s more, they’re tracking your phone, so they can tell exactly how many people from your country or region are in which area, at which time.

And they’re doing it in a bid to change tourism for the better.


Welcome to Venice in a post-Covid world. The canal city may have been known as La Serenissima, or The Most Serene, during its centuries ruling the waves as the powerful Republic of Venice.


In the past few years, however, things have become rather less serene, thanks to the almost 30 million visitors who descend each year on the city of just 50,000 inhabitants.
Before Covid-19 struck, tourists were arriving in often unmanageable numbers, choking the main streets and filling up the waterbuses.

Authorities had tried various measures, from introducing separate residents’ lines at major vaporetto (waterbus) stops to bringing in turnstiles that would filter locals from tourists on busy days. A planned “entrance tax,” due to debut in 2020, has been postponed to January 2022, due to the pandemic.
But as well as controlling footfall, the authorities wanted to track tourism itself — not just by registering overnight guests but, in a city where the vast majority of visitors are daytrippers, by counting exactly who is in the city — and where they go.


Enter the Venice Control Room.

On the island of Tronchetto, next to the two-mile bridge separating Venice from the Italian mainland, the Control Room opened in September 2020. A former warehouse that had been abandoned since the 1960s, it’s part of a new headquarters for the city’s police and government — a self-described “control tower” for the city.The building has offices for the mayor, other dignitaries, and a large CCTV room, with cameras feeding in images from around the city, watched over by the police.

This is the brain of the city,” says Marco Bettini, co-director general of Venis, the Venice-based multimedia and tech company which built the system.


“We know in real time how many people are in each part [of the city], and which countries they’re from.”
He clicks on the video feed from the Grand Canal — the “freeway” of Venice, as he calls it — to look at the traffic.


“There’s huge traffic pressure here,” he says. Public waterbuses, boats delivering goods, taxis, residents zipping up the “road” in their own, private boats, and, of course, those famous gondolas — they’re all jostling for space on the Grand Canal. With no designated lanes, it can be a free-for-all.

But the new system not only records what’s going on; it analyzes the traffic, recognizing the different types of boats, from gondola to a “topo” — essentially a water-truck. It then stores the numbers. And it even tallies with the public transportation timetables, logging if a waterbus is late and, if so, by how many minutes.


Workers can also activate a “time machine” to look back — so far today, for example, there have been more than 1,000 boats passing under the main bridge at Piazzale Roma, the main entry point to the city.
It’s the pedestrian numbers, however, that are of more interest to the authorities looking at tourism patterns.

The system not only counts visitors in the vicinity of cameras posted around the city, but it also, in conjunction with TIM (Telecom Italia, Italy’s largest telecommunications provider), crunches who they are and where they come from.

On this winter day, before the Veneto region entered another semi-lockdown, for example, so far, 13,628 people have entered Venice, and 8,548 have left. In the hour after 7am, 1,688 people arrived at Piazzale Roma (the gateway to the city by road and tram) — the commuters.
At 10am, the arrivals reached a peak of 2,411: most likely the daytrippers.

The authorities can see where these new arrivals are from by analyzing their phone data (the information is all aggregated automatically, so no personal details can be gleaned).


There are 97 people in the area around St Mark’s Square on this Saturday afternoon, according to Bettini — of which only 24 are not Italian.

And so far today there have been 955 people in the area, 428 of whom have come from abroad. Of the 527 Italians, only 246 are resident in Venice (if a mobile phone is regularly logged in the city, it is counted as a resident).


“As you can see, the number of daytrippers — is steep,” says Bettini. This is crucial information, because these “hit-and-run” tourists are usually charged with causing the most damage to the struggling city. They tend to come in from other parts of Italy — often from beach resorts on a bad weather day — and rarely spend money, bringing their own food and eating illicit picnics on bridges and on waterfronts. But since they don’t stay overnight, they cannot be counted by the authorities — until now.

Counting the daytrippers and tracking where they tend to visit, and which streets they take, could be crucial for a city which has resorted to closing its main thoroughfares to non-locals at busy times in an attempt to spread people throughout the city.


As Valeria Duflot, co-founder of Venezia Autentica an online social enterprise working on sustainable tourism, says: “The problem is not that Venice has too many visitors. The problem is that all the visitors go to the same two places: St Mark’s Square and the Rialto Bridge.”

Italians are logged by the region they live in. Of the foreigners, the system breaks down where they come from (data is based on where their mobile phone is registered, so most likely their country of origin), and displays them as bars on a map on the city — a graphic representation of overcrowding in real time, with colors going from white to red as the numbers get higher.


Today, 36% of foreign visitors are German, followed by the Swiss (16%) and British (13% — this visit took place before the new UK variant saw British travelers banned from Italy). Just 1.312% of visitors are from the United States — although, given that American travelers are still banned from the European Union, it’s a surprise it’s even that much.


And today, there have been 85,000 people logged in Venice. A much greater number, 177,000, have been in Mestre, on the mainland. On the islands — where places such as Burano and Murano are popular with tourists — there are 5,700 people, this Saturday afternoon.


There’s plenty more that the authorities are keeping tabs on: how fast people are moving in places like St Mark’s Square (start running and the machine highlights you), the tide levels throughout the lagoon (crucial for monitoring acqua alta flooding, and determining when the new Mose flood barriers should be raised).


The system took three years to build, at a cost of €3m ($3.5m). And although some might baulk at the privacy implications (although no personal data is recorded, you and your provenance is essentially being logged as you move around the city), the authorities are very proud.


“In 2021, Venice celebrates its 1,600th anniversary,” says Bettini. “And we’ll be celebrating with technology.”

Source: CNN

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